Cross-Sectional Studies ; Depression/epidemiology* ; Humans ; Job Satisfaction ; Occupational Stress/epidemiology* ; Oil and Gas Fields ; Stress, Psychological ; Surveys and Questionnaires

Objective: To analyze the epidemiological characteristics, dynamic trend of development and related influencing factors of hepatitis C in Shandong, China, 2007-2016, also to provide epidemiological evidence for prevention and control of HCV. Methods: National surveillance data of hepatitis C from 2007 to 2016 in Shandong was used, with distribution and clustering map of hepatitis C drawn at the county level. Panel Poisson regression was used to explore the influencing factors of hepatitis C at the city level. Results: The incidence of hepatitis C in Shandong increased from 1.49/100 000 in 2007 to 4.72/100 000 in 2016, with the high incidence mainly clustered in the urban regions in Jinan, Zibo, Weihai et al. and surrounding vicinities. Majority of the cases were young adults, with 53.16% (14 711/27 671) of them being farmers. Results from the Multiple panel Poisson regression analysis indicated that factors as: population density (aIRR=1.07, 95%CI: 1.05-1.10), number of hospital per hundred thousand people shared (aIRR=1.16, 95%CI: 1.08-1.24), expenditure of medical fee in rural (aIRR=1.21, 95%CI: 1.08-1.37) and the proportion of the tertiary industry (aIRR=1.08, 95%CI: 1.07-1.09) were all correlated to the incidence of hepatitis C. Conclusions: The incidence of hepatitis C had been increasing rapidly in recent years, in Shandong. Prevention and control of HCV should focus on high risk population. In addition, rural, especially in areas with lower economics provision should be under more attentions, so as to find more concealed cases for early treatment.
Adult ; China/epidemiology* ; Cities ; Hepacivirus ; Hepatitis C/prevention & control* ; Humans ; Incidence ; Population Surveillance ; Young Adult

Objective: To explore the association between nuclear factor kappa-light-chain-enhancer of activated genetic polymorphisms in B cells (NF-κB) and the HCV susceptibility, among the Chinese population. Methods: A total of 1 679 participants were enrolled; including 503 drug users and 1 176 other participants at risk under the exposure for blood. By using the logistic regression analysis, related risk factors for HCV infection among subjects were analyzed. Two NF-κB pathway variants, NF-κB1 rs72696119 and REL rs13031237 were then genotyped by TaqMan assay method. Logistic regression analysis was performed to analyze the association between gene polymorphisms and the susceptibility on HCV. Results: Among the drug users, women (OR=0.408, 95%CI: 0.308-0.767) appeared to be associated with the decreased risk for HCV infection, while factors as drug injection (OR=8.817, 95%CI: 5.577-13.937) and the duration of drug-intake >5.5 years (OR=2.891, 95%CI: 1.824-4.583) were associated with the increased risk for HCV infection. Among the participants who had been exposed to blood, women (OR=3.431, 95%CI: 2.360-4.988) were associated with the increased risk for HCV infection, while the levels of education beyond elementary school (OR=0.613, 95%CI: 0.429-0.876) were associated with the decreased risk for HCV infection. Compared to the reference NF-κB1 rs72696119 CC genotype, the carriage of GG genotype was associated with an increased risk of susceptibility on HCV (OR=1.412, 95%CI: 1.035-1.927) among the total study population. Results from the interaction analysis showed that there was no interactive effects appeared between rs72696119 and route of infection, or between rs72696119 and gender among the total population under study (all P>0.05). Conclusion: NF-κB1 polymorphism rs72696119 and related factors seemed associated with the susceptibility to HCV infection among high-risk Chinese populations.
Asian People/genetics* ; B-Lymphocytes ; Case-Control Studies ; China/epidemiology* ; Female ; Genetic Predisposition to Disease ; Hepatitis C/genetics* ; Humans ; Male ; Middle Aged ; NF-kappa B/genetics* ; Polymorphism, Single Nucleotide

To address the increasing need for detecting and validating protein biomarkers in clinical specimens, mass spectrometry (MS)-based targeted proteomic techniques, including the selected reaction monitoring (SRM), parallel reaction monitoring (PRM), and massively parallel data-independent acquisition (DIA), have been developed. For optimal performance, they require the fragment ion spectra of targeted peptides as prior knowledge. In this report, we describe a MS pipe-line and spectral resource to support targeted proteomics studies for human tissue samples. To build the spectral resource, we integrated common open-source MS computational tools to assemble a freely accessible computational workflow based on Docker. We then applied the workflow to gen-erate DPHL, a comprehensive DIA pan-human library, from 1096 data-dependent acquisition (DDA) MS raw files for 16 types of cancer samples. This extensive spectral resource was then applied to a proteomic study of 17 prostate cancer (PCa) patients. Thereafter, PRM validation was applied to a larger study of 57 PCa patients and the differential expression of three proteins in prostate tumor was validated. As a second application, the DPHL spectral resource was applied to a study consisting of plasma samples from 19 diffuse large B cell lymphoma (DLBCL) patients and 18 healthy control subjects. Differentially expressed proteins between DLBCL patients and healthy control subjects were detected by DIA-MS and confirmed by PRM. These data demonstrate that the DPHL supports DIA and PRM MS pipelines for robust protein biomarker discovery. DPHL is freely accessible at https://www.iprox.org/page/project.html?id=IPX0001400000.

Platelets are reprogrammed by cancer via a process called education, which favors cancer development. The transcriptional profile of tumor-educated platelets (TEPs) is skewed and therefore practicable for cancer detection. This intercontinental, hospital-based, diagnostic study included 761 treatment-naïve inpatients with histologically confirmed adnexal masses and 167 healthy controls from nine medical centers (China, n = 3; Netherlands, n = 5; Poland, n = 1) between September 2016 and May 2019. The main outcomes were the performance of TEPs and their combination with CA125 in two Chinese (VC1 and VC2) and the European (VC3) validation cohorts collectively and independently. Exploratory outcome was the value of TEPs in public pan-cancer platelet transcriptome datasets. The AUCs for TEPs in the combined validation cohort, VC1, VC2, and VC3 were 0.918 (95% CI 0.889-0.948), 0.923 (0.855-0.990), 0.918 (0.872-0.963), and 0.887 (0.813-0.960), respectively. Combination of TEPs and CA125 demonstrated an AUC of 0.922 (0.889-0.955) in the combined validation cohort; 0.955 (0.912-0.997) in VC1; 0.939 (0.901-0.977) in VC2; 0.917 (0.824-1.000) in VC3. For subgroup analysis, TEPs exhibited an AUC of 0.858, 0.859, and 0.920 to detect early-stage, borderline, non-epithelial diseases and 0.899 to discriminate ovarian cancer from endometriosis. TEPs had robustness, compatibility, and universality for preoperative diagnosis of ovarian cancer since it withstood validations in populations of different ethnicities, heterogeneous histological subtypes, and early-stage ovarian cancer. However, these observations warrant prospective validations in a larger population before clinical utilities.
Humans ; Female ; Blood Platelets/pathology* ; Biomarkers, Tumor/genetics* ; Ovarian Neoplasms/pathology* ; China